Related papers: Modelling Technique for GDPR-compliance: Toward a …
Physical persons playing the role of car drivers consume data that is sourced from the Internet and, at the same time, themselves act as sources of relevant data. It follows that citizens' privacy is potentially at risk while they drive,…
We increasingly rely on digital services and the conveniences they provide. Processing of personal data is integral to such services and thus privacy and data protection are a growing concern, and governments have responded with regulations…
Threat modeling has been successfully applied to model technical threats within information systems. However, a lack of methods focusing on non-technical assets and their representation can be observed in theory and practice. Following the…
Enterprises today face increasing cybersecurity threats that necessitate robust digital forensics and risk mitigation strategies. This paper explores these challenges through an imaginary case study of an organization, a global identity…
A core requirement for GDPR compliance is the maintenance of a register of processing activities (ROPA). Our analysis of six ROPA templates from EU data protection regulators shows the scope and granularity of a ROPA is subject to widely…
Processing personal data is regulated in Europe by the General Data Protection Regulation (GDPR) through data processing agreements (DPAs). Checking the compliance of DPAs contributes to the compliance verification of software systems as…
Model stealing attack is increasingly threatening the confidentiality of machine learning models deployed in the cloud. Recent studies reveal that adversaries can exploit data synthesis techniques to steal machine learning models even in…
With the General Data Protection Regulation (GDPR) in place, all domains have to ensure compliance with privacy legislation. However, compliance does not necessarily result in a privacy-friendly system as for example getting users' consent…
There is a known tension between the need to analyze personal data to drive business and privacy concerns. Many data protection regulations, including the EU General Data Protection Regulation (GDPR) and the California Consumer Protection…
Access to data and data processing, including the use of machine learning techniques, has become significantly easier and cheaper in recent years. Nevertheless, solutions that can be widely adopted by regulators for market monitoring and…
This article examines the principles outlined in the General Data Protection Regulation (GDPR) in the context of social network data. We provide both a practical guide to GDPR-compliant social network data processing, covering aspects such…
Cloud computing adoption across industries has revolutionized enterprise operations while introducing significant challenges in compliance management. Organizations must continuously meet evolving regulatory requirements such as GDPR and…
The Solid specification aims to empower data subjects by giving them direct access control over their data across multiple applications. As governments are manifesting their interest in this framework for citizen empowerment and…
Internet of Things (IoT) applications have the potential to derive sensitive information about individuals. Therefore, developers must exercise due diligence to make sure that data are managed according to the privacy regulations and data…
The General Data Protection Regulation contains a blanket prohibition on the transfer of personal data outside of the European Economic Area unless strict requirements are met. The rationale for this provision is to protect personal data…
User profiling is a critical component of adaptive risk-based authentication, yet it raises significant privacy concerns, particularly when handling sensitive data. Profiling involves collecting and aggregating various user features,…
Research on formulae production in spreadsheets has established the practice as high risk yet unrecognised as such by industry. There are numerous software applications that are designed to audit formulae and find errors. However these are…
Modern privacy regulations provide a strict mandate for data processing entities to implement appropriate technical measures to demonstrate compliance. In practice, determining what measures are indeed "appropriate" is not trivial,…
Threat modeling is a crucial component of cybersecurity, particularly for industries such as banking, where the security of financial data is paramount. Traditional threat modeling approaches require expert intervention and manual effort,…
Understanding how data quality aligns with regulatory requirements in machine learning (ML) systems presents a critical challenge for practitioners navigating the evolving EU regulatory landscape. To address this, we first propose a…